Impact of the Nutri-Score 2.0 on primary outcomes (ie, objective understanding of nutritional quality and food ultraprocessing), NutriNet-Santé, 2022, France, n=21 159
| OR* (95% CI) [experimental arm vs. control arm) | P-trend | |||
| All products | ||||
| Number of correct answers | 0–2 | 3–6 | 7–9 | |
| Understanding of nutritional quality | 1 | 0.54 (0.51–0.57) | 29.0 (23.4–35.9) | <0.0001 |
| Number of correct answers | 0–12 | 13–19 | 20–22 | |
| Understanding of ultraprocessing | 1 | 1.94 (1.75–2.14) | 174.3 (151.4–200.5) | <0.0001 |
| Cookies | ||||
| Number of correct answers | 0 | 1–2 | 3 | |
| Understanding of nutritional quality | 1 | 0.50 (0.47–0.53) | 6.46 (5.86–7.13) | <0.0001 |
| Number of correct answers | 0–4 | 5–7 | 8 | |
| Understanding of ultraprocessing | 1 | 1.89 (1.73–2.06) | 191.4 (164.2–223.1) | <0.0001 |
| Breakfast cereals | ||||
| Number of correct answers | 0 | 1–2 | 3 | |
| Understanding of nutritional quality | 1 | 2.75 (2.51–3.00) | 86.8 (70.2–107.3) | <0.0001 |
| Number of correct answers | 0–4 | 5–6 | 7 | |
| Understanding of ultraprocessing | 1 | 2.37 (2.16–2.60) | 35.6 (32.4–39.2) | <0.0001 |
| Ready-to-eat meals | ||||
| Number of correct answers | 0 | 1–2 | 3 | |
| Understanding of nutritional quality | 1 | 0.59 (0.56–0.63) | 17.3 (14.4–20.8) | <0.0001 |
| Number of correct answers | 0–4 | 5–6 | 7 | |
| Understanding of ultraprocessing | 1 | 2.38 (2.16–2.62) | 100.0 (89.5–111.7) | <0.0001 |
*ORs were derived from multinomial logistic regression models to predict the number of correct answers according to the experimentation arm, adjusted for age, sex, educational level, household monthly income, professional situation and area of residence